How homophonous are interlingual homophones? An acoustic and perceptual inquiry
Bibliographic record
Abstract
Interlingual homophones (IHs) are cross-linguistic word pairs with the “same” phonological forms but distinct meanings. This phonological similarity may lead to perceptual ambiguity for bilingual listeners. Prior studies have demonstrated that listeners can use language-specific phonetic cues to resolve IH ambiguity, but few have quantified the acoustic similarity or examined their perceptual distinctiveness in unilingual versus code-switching sentential contexts. This study investigates Mandarin–English IHs with both acoustic analysis and perception experiments. We hypothesize that (1) smaller acoustic distances between IH pairs will increase perceptual ambiguity, and (2) listeners will bias their interpretation toward the language of the carrier sentence. IH candidates were systematically extracted from corpora and recorded by a phonetically trained and highly proficient Mandarin–English bilingual. Acoustic similarity was quantified using absement. Perceptual judgments were collected using a Visual Analog Scale (VAS), with bilingual participants evaluating IHs presented in isolation and in Mandarin or English sentential contexts. Results are discussed in relation to acoustic distance, language-specific phonetic cue utilization, and sentence-level prediction in bilingual speech processing.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".